Lead the development of machine learning models for dynamic pricing and personalization, collaborating with multiple teams to optimize algorithms and enhance consumer experiences.
Role Overview:We seek a highly skilled Senior Applied Machine Learning Engineer to lead innovation in dynamic pricing algorithms, personalized offer systems, and intelligent product recommendations. You will work in a collaborative, cross-functional environment, building machine learning pipelines, deploying robust models, and designing AI agents that optimize pricing, conversion, and consumer experiences. You will partner with Product, Marketing, Sales and Engineering to align ML initiatives with strategic goals.
This is a Hybrid position based in Bangalore. You must be within a commutable distance from the location. You will be required to be onsite on an as-needed basis; when not working onsite, you will work remotely from your home location.
Company Overview
This is a Hybrid position based in Bangalore. You must be within a commutable distance from the location. You will be required to be onsite on an as-needed basis; when not working onsite, you will work remotely from your home location.
About the Role:
- Architect, prototype and productionize ML models for dynamic pricing, personalization and retention optimization.
- Lead advanced traditional ML (e.g., XGBoost, Random Forest, SVM) initiatives, applying intermediate to advanced statistical interpretation to validate and explain model outputs.
- Design causal‐inference frameworks, A/B and multivariate tests to validate model efficacy.
- Analyze test results and iterate rapidly to maximize business KPIS.
- Implement Multi-Armed Bandits, Contextual Bandits, Thompson Sampling, Q-learning/SARSA, and Bayesian Optimization algorithms.
About You:
- Time Zone Support: Comfortable working actively during the given period - (1:30 PM–10:30 PM IST) and collaborating effectively with global teams across multiple time zones.
- Preferably Master’s or Ph.D. in Machine Learning, Computer Science, Statistics, or a related quantitative field (preferred) with 6 to 8 years in applied machine learning with at least 3 years in a senior or leadership role.
- Implementing AI/ML personalization techniques to enhance consumer/customer product experiences.
- Developing AI/ML-based dynamic pricing and personalized-offer strategies for pricing optimization.
- Creating customer/consumer churn and propensity models specifically for digital subscription use cases.
- Proficient in Python and SQL (advanced queries, window functions) and with hands-on with scikit-learn, TensorFlow, PyTorch or Keras.
- Deep understanding of classical ML (XGBoost, Random Forest, SVM) and RL techniques (e.g., Contextual Bandits, Thompson Sampling, Q-learning).
- Familiarity with big-data ecosystems (Hadoop, Hive) and MLOps/deployment pipelines.
#LI- Hybrid
Company Overview
McAfee is a leader in personal security for consumers. Focused on protecting people, not just devices, McAfee consumer solutions adapt to users’ needs in an always online world, empowering them to live securely through integrated, intuitive solutions that protects their families and communities with the right security at the right moment.
Company Benefits and Perks:We work hard to embrace diversity and inclusion and encourage everyone at McAfee to bring their authentic selves to work every day. We offer a variety of social programs, flexible work hours and family-friendly benefits to all of our employees.
- Bonus Program
- Pension and Retirement Plans
- Medical, Dental and Vision Coverage
- Paid Time Off
- Paid Parental Leave
- Support for Community Involvement
We're serious about our commitment to diversity which is why McAfee prohibits discrimination based on race, color, religion, gender, national origin, age, disability, veteran status, marital status, pregnancy, gender expression or identity, sexual orientation or any other legally protected status.
Top Skills
Hadoop
Hive
Keras
Python
PyTorch
Random Forest
SQL
Svm
TensorFlow
Xgboost
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